Search results for: web application architecture

Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida

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This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatio-temporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.

Keywords: WSN, database spatio-temporal, GIS, web mapping, indicator of drought

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Authors: Pooya Niksiar, Ali Ashrafizadeh, Mehrzad Shams, Amir Hossein Madani

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There are many computationally demanding applications in science and engineering which need efficient algorithms implemented on high performance computers. Recently, Graphics Processing Units (GPUs) have drawn much attention as compared to the traditional CPU-based hardware and have opened up new improvement venues in scientific computing. One particular application area is Computational Fluid Dynamics (CFD), in which mature CPU-based codes need to be converted to GPU-based algorithms to take advantage of this new technology. In this paper, numerical solutions of two classes of discrete fluid flow models via both CPU and GPU are discussed and compared. Test problems include an Eulerian model of a two-dimensional incompressible laminar flow case and a Lagrangian model of a two phase flow field. The CUDA programming standard is used to employ an NVIDIA GPU with 480 cores and a C++ serial code is run on a single core Intel quad-core CPU. Up to two orders of magnitude speed up is observed on GPU for a certain range of grid resolution or particle numbers. As expected, Lagrangian formulation is better suited for parallel computations on GPU although Eulerian formulation represents significant speed up too.

Keywords: CFD, Eulerian formulation, graphics processing units, Lagrangian formulation

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Authors: O. Kahraman, M. S. Alatas, O. B. Citil

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In determination of values of feeds which, are used in ruminant nutrition, different methods are used like in vivo, in vitro, in situ or in sacco. Generally, the most reliable results are taken from the in vivo studies. But because of the disadvantages like being hard, laborious and expensive, time consuming, being hard to keep the experiment conditions under control and too much samples are needed, the in vitro techniques are more preferred. The most widely used in vitro techniques are two-staged digestion technique and gas production technique. In vitro gas production technique is based on the measurement of the CO2 which is released as a result of microbial fermentation of the feeds. In this review, the factors affecting the results obtained from in vitro gas production technique (Hohenheim Feed Test) were discussed. Some factors must be taken into consideration when interpreting the findings obtained in these studies and also comparing the findings reported by different researchers for the same feeds. These factors were discussed in 3 groups: factors related to animal, factors related to feeds and factors related with differences in the application of method. These factors and their effects on the results were explained. Also it can be concluded that the use of in vitro gas production technique in feed evaluation routinely can be contributed to the comprehensive feed evaluation, but standardization is needed in this technique to attain more reliable results.

Keywords: In vitro, gas production technique, Hohenheim feed test, standardization

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Authors: Angie Quevedo, Juan Bussi, Nestor Tancredi, Juan Fajardo-Díaz, Florentino López-Urías, Emilio Muñóz-Sandoval

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In this work, we study the carbon nanotubes (CNTs) formation by catalytic chemical vapor deposition (CCVD) over a catalyst with 20 % of Ni supported over La₂Zr₂O₇ (Ni20LZO). The high C solubility of Ni made it one of the most used in CNTs synthesis. Nevertheless, Ni presents also sintering and coalescence at high temperature. These troubles can be reduced by choosing a suitable support. We propose La₂Zr₂O₇ as for this matter since the incorporation of Ni by co-precipitation and calcination at 900 °C allows a good dispersion and interaction of the active metal (in the oxidized form, NiO) with this support. The CCVD was performed using 1 g of Ni20LZO at 950 °C during 30 min in Ar:H₂ atmosphere (2.5 L/min). The precursor, benzylamine, was added by a nebulizer-sprayer. X ray diffraction study shows the phase separation of NiO and La₂Zr₂O₇ after the calcination and the reduction to Ni after the synthesis. Raman spectra show D and G bands with a ID/IG ratio of 0.75. Elemental study verifies the incorporation of 1% of N. Thermogravimetric analysis shows the oxidation process start at around 450 °C. Future studies will determine the application potential of the samples.

Keywords: N doped carbon nanotubes, catalytic chemical vapor deposition, nickel catalyst, bimetallic oxide

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Authors: Yong Ho Jeon, Youn Mi Lee, Yong Yoon Lee

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Effects of cold plasma treatment on various plant seed germination were studied. The seeds of hot pepper, cucumber, tomato and arabidopsis were exposed to plasma and the plasma was generated in various devices. The germination speed was evaluated compared to an unexposed control. A positive effect on germination speed was observed in all tested seeds but the effects strongly depended on the type of the used plasma device (Argon-DBD, surface-DBD or MARX generator), time of exposure (6s~10min or 1~10shots) and kind of seeds. The SEM images showed that arrays of gold particles along the cell wall were observed on the surface of cucumber seeds showed a germination-accelerating effect by plasma treatment, which was the same as untreated. However, when treated with the high dose plasma, gold particles were not arrayed at the seed surface, it seems that due to the surface etching. This may suggest that the germination is not promoted by etching or damage of surface caused by the plasma treatment. Seedling growth improvement was also observed by indirect plasma treatment. These lead to an important conclusion that the effect of charged particles on plasma play the essential role in plant germination and indirect plasma treatment offers new perspectives for large scale application.

Keywords: cold plasma, cucumber, germination, SEM

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Authors: Ali M. Zaid, Muftah Mayouf, Yahya Said Farouj

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The effect of post emergence herbicides on soil micro-flora and nitrogen fixing bacteria was studied in pea field. Pea (Pisum sativum) was grown and treated with one or a mixture of two of several herbicides 2 weeks after sowing. Soil samples were collected 2 weeks after herbicides application. Average number of colony forming units per gram of soil of bacteria, actinomycetes and fungi were determined. Average number of nodules per plant was obtained at the end of the growing season. The results of the study showed MCPB, Bentazon, MCPB+Fluozifop-p-butyl, Bentazon+Fluozifop-p-butyl, Metribuzin, Flouzifop-p-butyl+Metribuzin, Cycloxydin, and Sethoxydin increased the population of soil fungi, with 4 to 10 times compared with the control. The herbicides used showed no significant effects on nitrogen fixing bacteria. The effects of herbicides on soil bacteria and actinomycetes were different. The study showed the use of herbicides could influence the biological balance of soil microflora, which has an important role in soil fertility and microbial ecosystem.

Keywords: herbicides, post emergence, nitrogen fixing bacteria, environmental systems

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Authors: Folorunso Omoniyi, Peter Olubambi, Rotimi Sadiku

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Thermal barrier coating (TBC) system is used in both aero engines and other gas turbines to offer oxidation protection to superalloy substrate component. In the present work, it shows the ability of a new fabrication technique to develop rapidly new coating composition and microstructure. The compact powders were prepared by Powder Metallurgy method involving powder mixing and the bond coat was synthesized through the application of Spark Plasma Sintering (SPS) at 10500C to produce a fully dense (97%) NiCrAl bulk samples. The influence of sintering temperature on the hardness of NiCrAl, done by Micro Vickers hardness tester, was investigated. And Oxidation test was carried out at 1100oC for 20h, 40h, and 100h. The resulting coat was characterized with optical microscopy, scanning electron microscopy (SEM), energy dispersive x-ray analysis (EDAX) and x-ray diffraction (XRD). Micro XRD analysis after the oxidation test revealed the formation of protective oxides and non-protective oxides.

Keywords: high-temperature oxidation, powder metallurgy, spark plasma sintering, thermal barrier coating

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Authors: Marjan Ghazisaeedi, Azadeh Bashiri

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Background: Attention-Deficit/Hyperactivity Disorder(ADHD), is one of the most common psychiatric disorders in early childhood that in addition to its main symptoms provide significant deficits in the areas of educational, social and individual relationship. Considering the importance of rehabilitation in ADHD patients to control these problems, this study investigated the advantages of computer-based cognitive training in these patients. Methods: This review article has been conducted by searching articles since 2005 in scientific databases and e-Journals and by using keywords including computerized cognitive rehabilitation, computer-based training and ADHD. Results: Since drugs have short term effects and also they have many side effects in the rehabilitation of ADHD patients, using supplementary methods such as computer-based cognitive training is one of the best solutions. This approach has quick feedback and also has no side effects. So, it provides promising results in cognitive rehabilitation of ADHD especially on the working memory and attention. Conclusion: Considering different cognitive dysfunctions in ADHD patients, application of the computerized cognitive training has the potential to improve cognitive functions and consequently social, academic and behavioral performances in patients with this disorder.

Keywords: ADHD, computer-based cognitive training, cognitive functions, rehabilitation

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Authors: Esraa Moustafa, Gaetan Rey, Stephane Lavirotte, Jean-Yves Tigli

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With the development of Internet of Things and Web of Things, computing becomes more pervasive, invisible and present everywhere. In fact, in our environment, we are surrounded by multiple devices that deliver (web) services that meet the needs of the users. However, the mobility of these devices as the users has important repercussions that challenge software design of these applications because the variability of the environment cannot be anticipated at the design time. Thus, it will be interesting to dynamically discover the environment and adapt the application during its execution to the new contextual conditions. We, therefore, propose a model of a context-aware middleware that can address this issue through a monitoring service that is capable of reasoning and observation channels capable of calculating the context during the runtime. The monitoring service evaluates the pre-defined X-Query predicates in the context manager and uses Prolog to deduce the services needed to respond back. An independent Observation Channel for each different predicate is then dynamically generated by the monitoring service depending on the current state of the environment. Each channel sends its result directly to the context manager which consequently calculates the context based on all the predicates’ results while preserving the reactivity of the self-adaptive system.

Keywords: auto-adaptation, context-awareness, middleware, reasoning engine

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Cinthia Campoverde, Mateo Benavidez, Victor Arias, Milton Torres

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This article evaluates and compares three propagation models: the Okumura-Hata model, the Ericsson 9999 model, and the SUI model. The inclusion of vegetation attenuation in the area is also taken into account. These mathematical models aim to predict the power loss between a transmitting antenna (Tx) and a receiving antenna (Rx). The study was conducted in the open areas of the Livestock Department at the Escuela Superior Politécnica de Chimborazo (ESPOCH) University, located in the city of Riobamba, Ecuador. The necessary parameters for each model were calculated, considering LTE technology. The transmitting antenna belongs to the mobile phone company ”TUENTI” in Band 2, operating at a frequency of 1940 MHz. The reception power data in the area were empirically measured using the ”Network Cell Info” application. A total of 170 samples were collected, distributed across 19 radius, forming concentric circles around the transmitting antenna. The results demonstrate that the Okumura Hata urban model provides the best fit to the measured data.

Keywords: propagation models, reception power, LTE, power losses, correction factor

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Authors: Tatsuya Otoshi, Masayuki Murata

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With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.

Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm

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Authors: Hadi Rouhi Belvirdi, Davoud Beheshtizadeh

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The increasing demand for sustainable construction materials has led to a growing interest in high-strength recycled concrete (HSRC). Utilizing recycled materials not only reduces waste but also minimizes the depletion of natural resources. This study explores the application of artificial intelligence (AI) techniques to model and predict the properties of HSRC. In the past two decades, the production levels in various industries and, consequently, the amount of waste have increased significantly. Continuing this trend will undoubtedly cause irreparable damage to the environment. For this reason, engineers have been constantly seeking practical solutions for recycling industrial waste in recent years. This research utilized the results of the compressive strength of 90-day high-strength recycled concrete. The method for creating recycled concrete involved replacing sand with crushed glass and using glass powder instead of cement. Subsequently, a feedforward artificial neural network was employed to model the compressive strength results for 90 days. The regression and error values obtained indicate that this network is suitable for modeling the compressive strength data.

Keywords: high-strength recycled concrete, feedforward artificial neural network, regression, construction materials

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Authors: Madhuresh Dwivedi, Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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FT-NIR spectroscopy and electronic nose was used to study the kinetics of dough proofing. Spectroscopy was conducted with an optic probe in the diffuse reflectance mode. The dough leavening was carried out at different temperatures (25 and 35°C) and constant RH (80%). Spectra were collected in the range of wave numbers from 12,000 to 4,000 cm-1 directly on the samples, every 5 min during proofing, up to 2 hours. NIR spectra were corrected for scatter effect and second order derivatization was done to transform the spectra. Principal component analysis (PCA) was applied for the leavening process and process kinetics was calculated. PCA was performed on data set and loadings were calculated. For leavening, four absorption zones (8,950-8,850, 7,200-6,800, 5,250-5,150 and 4,700-4,250 cm-1) were involved in describing the process. Simultaneously electronic nose was also used for understanding the development of odour compounds during fermentation. The electronic nose was able to differential the sample on the basis of aroma generation at different time during fermentation. In order to rapidly differentiate samples based on odor, a Principal component analysis is performed and successfully demonstrated in this study. The result suggests that electronic nose and FT-NIR spectroscopy can be utilized for the online quality control of the fermentation process during leavening of bread dough.

Keywords: FT-NIR, dough, e-nose, proofing, principal component analysis

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Authors: Stephen Akong Takim

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This study focused on the optimization of the flexural strength of bio-composite samples of palm kernel, whelks, clams, periwinkles shells and bamboo fiber reinforced with resin for engineering applications. The aim of the study was to formulate different samples of bio-composite reinforced with resin for engineering applications and to evaluate the flexural strength of the fabricated composite. The hand lay-up technique was used for the composites produced by incorporating different percentage compositions of the shells/fiber (10%, 15%, 20%, 25% and 30%) into varied proportions of epoxy resin and catalyst. The cured samples, after 24 hours, were subjected to tensile, impact, flexural and water absorption tests. The experiments were conducted using the Taguchi optimization method L25 (5x5) with five design parameters and five level combinations in Minitab 18 statistical software. The results showed that the average value of flexural was 114.87MPa when compared to the unreinforced 72.33MPa bio-composite. The study recommended that agricultural waste, like palm kernel shells, whelk shells, clams, periwinkle shells and bamboo fiber, should be converted into important engineering applications.

Keywords: bio-composite, resin, palm kernel shells, welk shells, periwinkle shells, bamboo fiber, Taguchi techniques and engineering application

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Authors: J. Ptačinová, J. Ďurica, P. Jurči, M Kusý

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Ledeburitic tool steel Vanadis 6 has been subjected to sub-zero treatment (SZT) at -140 °C and -196 °C, for different durations up to 48 h. The microstructure and hardness have been examined with reference to the same material after room temperature quenching, by using the light microscopy, scanning electron microscopy, X-ray diffraction, and Vickers hardness testing method. The microstructure of the material consists of the martensitic matrix with certain amount of retained austenite, and of several types of carbides – eutectic carbides, secondary carbides, and small globular carbides. SZT reduces the retained austenite amount – this is more effective at -196 °C than at -140 °C. Alternatively, the amount of small globular carbides increases more rapidly after SZT at -140 °C than after the treatment at -140 °C. The hardness of sub-zero treated material is higher than that of conventionally treated steel when tempered at low temperature. Compressive hydrostatic stresses are developed in the retained austenite due to the application of SZT, as a result of more complete martensitic transformation. This is also why the population density of small globular carbides is substantially increased due to the SZT. In contrast, the hardness of sub-zero treated samples decreases more rapidly compared to that of conventionally treated steel, and in addition, sub-zero treated material induces a loss the secondary hardening peak.

Keywords: microstructure, Vanadis 6 tool steel, sub-zero treatment, carbides

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Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

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Authors: P. Singh, R. M. Banik

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Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.

Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Michael Sunday Afolayan

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This research work examined the challenges bedevilling the development of legal framework for electronic commercial transactions (e-commerce) in Nigeria. Nigeria does not have a clear-cut legislation regulating electronic commerce in its jurisdiction despite the geometrical rate of growth and adoption of this method of trade. It specifically posed a great challenge looking at taxation, evidential and jurisdictional issues in e-commerce in Nigeria. The author in a broader research work which is abridged here, traced the origin and development of e-commerce and the attendant laws applicable in Nigeria, examining their sufficiency or otherwise. In carrying out the research work, doctrinal mode of legal research was adopted, examining both primary and secondary sources of legal research materials within their contextual meanings. It was found that the failure to enact a law which has direct regulatory bearing on e-commerce in Nigeria has led to adoption and application of circumstantial laws, rules and common law principles to tackle the problems arising out of electronic commercial transactions, especially in the areas of taxation, evidential and jurisdictional challenges. It was ultimately suggested that there is urgent need to sign into law, the Electronic Transaction Bill which had already been passed by the National Assembly since 2017.

Keywords: e-commerce, legislation, taxation, evidential, jurisdiction

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Authors: Yongjian Du, Jinhua Sun, Kim M. Liew, Huahua Xiao

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Optimal allocation of emergency resources before a disaster is of great importance for emergency response. In reality, the pre-protection for a single critical node where accidents may occur is common. In this study, a model is developed to determine location and inventory decisions of multiple emergency resources among a set of candidate stations to minimize the total cost based on the constraints of budgetary and capacity. The total cost includes the economic accident loss which is accorded with probability distribution of time and the warehousing cost of resources which is increasing over time. A ratio is set to measure the degree of a storage station only serving the target node that becomes larger with the decrease of the distance between them. For the application of linear program, it is assumed that the length of travel time to the accident scene of emergency resources has a linear relationship with the economic accident loss. A computational experiment is conducted to illustrate how the proposed model works, and the results indicate its effectiveness and practicability.

Keywords: emergency response, integer linear program, multiple emergency resources, pre-allocation decisions, single potential accident node

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Authors: Fariba Azizi, Firoozeh Haghighi, Viliam Makis

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In this paper, we propose a method to model the relationship between failure time and degradation for a simple step stress test where underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to shorten failure time of products and a tampered failure rate (TFR) model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates (MLEs) of the model parameters are obtained through an expectation-maximization (EM) algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real example is analyzed to illustrate the application of the proposed methods.

Keywords: cause of failure, linear degradation path, reliability function, expectation-maximization algorithm, intensity, masked data

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Authors: Joud Zagzoog, Amira Aldabbagh, Radiyah Hamidaddin

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This research aims to test out and observe whether artificial intelligence (AI) software and applications could actually be effective, useful, and time-saving for those who use them. Shaguf Bites, a web application that uses AI technology, claims to help students study and memorize information more effectively in less time. The website uses smart learning, or AI-powered bite-sized repetitive learning, by transforming documents or PDFs with the help of AI into summarized interactive smart flashcards (Bites, n.d.). To properly test out the websites’ effectiveness, both qualitative and quantitative methods were used in this research. An experiment was conducted on a number of students where they were first requested to use Shaguf Bites without any prior knowledge or explanation of how to use it. Second, they were asked for feedback through a survey on how their experience was after using it and whether it was helpful, efficient, time-saving, and easy to use for studying. After reviewing the collected data, we found out that the majority of students found the website to be straightforward and easy to use. 58% of the respondents agreed that the website accurately formulated the flashcard questions. And 53% of them reported that they are most likely to use the website again in the future as well as recommend it to others. Overall, from the given results, it is clear that Shaguf Bites have proved to be very beneficial, accurate, and time saving for the majority of the students.

Keywords: artificial intelligence (AI), education, memorization, spaced repetition, flashcards.

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Authors: M. Kumpugdee-Vollrath, J.-P. Krause, S. Bürk

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Most of the drugs used for pharmaceutical purposes are poorly water-soluble drugs. About 40% of all newly discovered drugs are lipophilic and the numbers of lipophilic drugs seem to increase more and more. Drug delivery systems such as nanoparticles, micelles or liposomes are applied to improve their solubility and thus their bioavailability. Besides various techniques of solubilization, oil-in-water emulsions are often used to incorporate lipophilic drugs into the oil phase. To stabilize emulsions surface active substances (surfactants) are generally used. An alternative method to avoid the application of surfactants was of great interest. One possibility is to develop O/W-emulsion without any addition of surface active agents or the so called “surfactant-free emulsion or SFE”. The aim of this study was to develop and characterize SFE as a drug carrier by varying the production conditions. Lidocaine base was used as a model drug. The injection method was developed. Effects of ultrasound as well as of temperature on the properties of the emulsion were studied. Particle sizes and release were determined. The long-term stability up to 30 days was performed. The results showed that the surfactant-free O/W emulsions with pharmaceutical oil as drug carrier can be produced.

Keywords: emulsion, lidocaine, Miglyol, size, surfactant, light scattering, release, injection, ultrasound, stability

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Authors: Erika Tatiana Paredes Prada, Diana Marina Camargo Lemos

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Introduction: Recreovía as a public health strategy contributes to encourage the practice and adherence to physical activity (PA) recommendations, by temporarily closing the roads to motorized vehicles. The determination of the PA requires the evaluation of the reliability of the measurement instruments, in order to sustain the continuity and relevance of Recreovía as a community intervention. Objective: Establish the inter-rater reliability of the App for the System for Observing Play and Recreation in Communities (iSOPARC®) in the Recreovía of Bucaramanga, Colombia. Methods: Five trained observers at two observation points on the 2.3 km of the Recreovía (14th Street and 32nd Street) used the App (iSOPARC®), between 08:00 a.m. and 12:00 m. in periods of 20 minutes during a regular Sunday. Reliability analysis was performed using the Intraclass Correlation Coefficient (ICC 2.1). Results: A total of 2682 users were observed (43.6 % women) in 7 observations. ICC showed a range between 0.96 and 0.99 for the PA level and ICC between 0.95 and 0.99 for age group for the two observation points. Conclusion: The reliability found for the iSOPARC® guarantees the consecutive measurement of the PA level at the Recreovía, which will allow measuring it is effectiveness in the medium and long term, as a community intervention strategy.

Keywords: environment, observation, physical activity, recreation, reliability

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Authors: Hadjoui Abdelhamid, Saimi Ahmed

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The hybrid h-p finite element method for the dynamic behavior of nonlinear rotors is described in this paper. The standard h-version method of discretizing the problem is retained, but modified to allow the use of polynomially-enriched beam elements. A hierarchically enriching element will thus not affect the nodal displacement and rotation, but will influence the values of the nodal bending moment and shear force is used. The deterministic movements of rotation and translation of the support which are coupled to the excitations due to unbalance are also taken into account. We study also the geometric dissymmetry of the shaft and the disc, thus the equations of motion of the rotor contain variable parametric coefficients over time that can lead to a lateral dynamic instability. The effects of movements combined support for bearings are analyzed and discussed through Campbell diagrams and spectral analyses. A program is made in Matlab. After validation of the program, several examples are studied. The influence of physical and geometric parameters on the natural frequencies of the shaft is determined through the study of these examples. Among these parameters, we include the variation in the diameter and the thickness of the rotor, the position of the disc.

Keywords: Campbell diagram, critical speeds, nonlinear rotor, version h-p of FEM

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: John Segars

Abstract:

Built out of a real-world need to have better, more detailed, asset and infrastructure documentation, this project will lay out the case for using the database functionality of ArcGIS as a tool to track and maintain infrastructure location, status, maintenance and serviceability. Workflows and processes will be presented and detailed which may be applied to an organizations’ infrastructure needs that might allow them to make use of the robust tools which surround the ArcGIS platform. The end result is a value-added information system framework with a geographic component e.g., the spatial location of various I.T. assets, a detailed set of records which not only documents location but also captures the maintenance history for assets along with photographs and documentation of these various assets as attachments to the numerous feature class items. In addition to the asset location and documentation benefits, the staff will be able to log into the devices and pull SNMP (Simple Network Management Protocol) based query information from within the user interface. The entire collection of information may be displayed in ArcGIS, via a JavaScript based web application or via queries to the back-end database. The project is applicable to all organizations which maintain an IT infrastructure but specifically targets post-secondary educational institutions where access to ESRI resources is generally already available in house.

Keywords: ESRI, GIS, infrastructure, network documentation, PostgreSQL

Procedia PDF Downloads 184

Authors: Michael Adedotun Oke

Abstract:

In Nigeria, Bamboo is one of the most socioeconomically beneficial farming crops, with yearly investment returns of up to N1.6 million. Growing bamboo is a fantastic long-term investment. It may self-renew for up to 70 years and is durable, long-lasting, and environmentally friendly; through an oral interview with the sellers, usage examples, and visual depiction to support those examples, The paper was able to discuss the different uses for bamboo. The various field observations in Federal Capital Territory, including the electric poles, buildings, paper production, and decoration, from picture frames to room dividing screens, bamboo can make some elegant and exotic decorations for the home, building, furniture, cooking, agriculture, instrument, in construction for flooring, roofing designing, scaffolding, garden planting, even to control erosion and slope stabilization in erosion are observed. The use of it is multiplexed with straightforward man-made technology, in contrast. 'This study wants more innovative practices that will be able to make it lucrative for business purposes and sustainability of the process. Although there are various uses and requirements for growing bamboo successfully, it is advised to receive the proper training and in-depth understanding of the growth and management procedures. Consult an experienced bamboo farmer for help.

Keywords: bamboo, use, Nigeria, socioeconomically

Procedia PDF Downloads 72

Authors: Bishakha Majumdar, Ranjeet Nambudiri

Abstract:

Considerable dichotomy exists in research regarding the role of optimism and self-efficacy in work and career outcomes. Optimism and self-efficacy are related to performance, commitment and engagement, but also are implicated in seeing opportunities outside the firm and switching jobs. There is absence of research capturing these opposing strands of findings in the same model and providing a holistic understanding of how the expectancy beliefs operate in case of the working professional. We attempt to bridge this gap by proposing that career-decision self-efficacy and career outcome expectations affect intention to quit through the competitive mediation pathways of internal and external marketability. This model provides a holistic picture of the role of career expectancy beliefs on career outcomes, by considering perceived career opportunities both inside and outside one’s present organization. The understanding extends the application of career expectancy beliefs in the context of career decision-making by the employed individual. Further, it is valuable for reconsidering the effectiveness of hiring and retention techniques used by a firm, as selection, rewards and training programs need to be supplemented by interventions that specifically strengthen the stability pathway.

Keywords: career decision self-efficacy, career outcome expectations, marketability, intention to quit, job mobility

Procedia PDF Downloads 637